Machine Learning Engineer II

Uber

Confirmed live yesterday Low trust

Hybrid

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Work type: Hybrid
Location: Sunnyvale, CA
Posted: 77 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

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About Uber

Uber Technologies, Inc. is the world’s largest, San Francisco-based mobile technology platform facilitating on-demand ride-hailing, food delivery (Uber Eats), and freight transportation across approximately 70 countries.

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TL;DR · Machine Learning Engineer II

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JOB TITLE: Machine Learning Engineer II - AV Labs As a Machine Learning Engineer II - AV Labs, you will join a multi-disciplinary team focused on unlocking real-world, long-tail driving data for autonomous technology. You will work on Physical AI, developing advanced autonomy algorithms and foundation models to extract high-fidelity semantic meaning from complex urban edge cases. Your daily responsibilities include implementing scalable ML systems, managing upstream sensor dependencies, and delivering high-quality datasets through advanced sensor data collection, processing, and auto-labeling. You will also perform deep scene understanding and causal modeling of ego vehicle behavior. The role requires proficiency in Python, Linux environments, and modern AI/ML frameworks like PyTorch. Preferred skills include C++, high-performance computing, and experience deploying ML models in safety-critical physical systems within the autonomous driving domain.

What does a Machine Learning Engineer earn in California?

Median $235750 from 200 postings across 34 companies.

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Skills

Python PyTorch C++ Linux Machine Learning Computer Vision Robotics High-Performance Computing System Design Algorithm Development Data Mining Auto-labeling Physical AI Causal Modeling

What you'll do

Develop algorithms and foundation models to extract semantic meaning from complex urban edge cases.
Implement scalable machine learning systems and manage upstream sensor dependencies.
Deliver high-quality datasets through advanced sensor data collection and processing.
Develop auto-labeling systems to accelerate the development of machine learning technologies.
Build models for deep scene understanding and causal modeling of ego vehicle behavior.
Deploy advanced machine learning techniques into production environments.
Identify complex edge cases and provide robust algorithmic solutions for autonomous driving.

What we're looking for

2+ years of working experience in the ML/Robotics industry.
Bachelor’s degree or higher in Computer Science, Computer Engineering, or related fields.
Proficiency in Python and Linux environments.
Familiarity with modern AI/ML frameworks such as PyTorch.
Experience in the Autonomous Driving domain (preferred).
Proven track record of deploying ML models in safety-critical physical systems (preferred).
Master’s or PhD degree in Computer Vision, Robotics, or Machine Learning (preferred).
Familiarity with C++ and high-performance computing (preferred).